Introduction:
Meniscus has always been the focus of sport medicine with thousands of articles published annually. Few study has tried to analyze these papers with bibliometric methods. The purpose of ...this study is to statistically analyze the output of meniscus research and determine emerging research trends and hot spots.
Methods:
Papers related to the meniscus published from 2010 to 2019 were downloaded from the Web of Science Core Collection. Information about annual publications and journal distribution was analyzed by Excel 2016. Co-occurrence analysis of the countries/regions, institutions, authors, and keywords were performed with CiteSpace V, which was also used to perform a co-cited analysis of the references and generate corresponding knowledge maps as well as detect burst keywords.
Results:
A total of 10,066 articles regarding meniscus were published between 2010 and 2019. The number of articles annual about meniscus increased from 786 to 1300. Knee Surgery Sports Traumatology Arthroscopy, the United States, University of Pittsburgh, and LaPrade RF were journal, country, institution, and author with the most publications, respectively. Makris EA et al. in 2011 was the most cited articles, with a citation of 198. Osteoarthritis, tear repair, anterior cruciate ligament, and articular cartilage were keywords with occurrence of more than 500. Meniscal extrusion, scaffold, and tissue engineering were terms with most burst strength.
Conclusions:
Meniscus-related publications showed a gradual rising trend from 2010 to 2019. Osteoarthritis, tear repairs, and the anterior cruciate ligament are the current research hot spots. Extrusion and scaffolds may be the frontiers of meniscus research in the next few years.
Level of evidence:
IV.
Open burning of agricultural crop residues is widespread across eastern
China, and during certain post-harvest periods this activity is believed to
significantly influence air quality. However, the ...exact contribution of crop
residue burning to major air quality exceedances and air quality episodes
has proven difficult to quantify. Whilst highly successful in many regions,
in areas dominated by agricultural burning, MODIS-based (MODIS: Moderate Resolution Imaging
Spectroradiometer) fire emissions
inventories such as the Global
Fire Assimilation System (GFAS) and Global Fire Emissions Database (GFED) are suspected of significantly
underestimating the magnitude of biomass burning emissions due to the
typically very small, but highly numerous, fires involved that are quite
easily missed by coarser-spatial-resolution remote sensing observations. To
address this issue, we use twice-daily fire radiative power (FRP)
observations from the “small-fire-optimised” VIIRS-IM FRP product and
combine them with fire diurnal cycle information taken from the geostationary
Himawari-8 satellite. Using this we generate a unique high-spatio-temporal-resolution agricultural burning inventory for eastern China for the years
2012–2015, designed to fully take into account small fires well below the
MODIS burned area or active fire detection limit, focusing on dry matter
burned (DMB) and emissions of CO2, CO, PM2.5, and black carbon. We
calculate DMB totals 100 % to 400 % higher than reported by the GFAS and
GFED4.1s, and we quantify interesting spatial and temporal patterns previously
un-noted. Wheat residue burning, primarily occurring in May–June, is
responsible for more than half of the annual crop residue burning emissions
of all species, whilst a secondary peak in autumn (September–October) is associated
with rice and corn residue burning. We further identify a new winter
(November–December) burning season, hypothesised to be caused by delays in burning
driven by the stronger implementation of residue burning bans during the
autumn post-harvest season. Whilst our emissions estimates are far higher
than those of other satellite-based emissions inventories for the region,
they are lower than estimates made using traditional “crop-yield-based
approaches” (CYBAs) by a factor of between 2 and 5. We believe that this is
at least in part caused by outdated and overly high burning ratios being
used in the CYBA, leading to the overestimation of DMB. Therefore,
we conclude that satellite remote sensing approaches which adequately
detect the presence of agricultural fires are a far better approach to
agricultural fire emission estimation.
Abstract
Prostate cancer (PCa) affects millions of men globally. Due to advances in understanding genomic landscapes and biological functions, the treatment of PCa continues to improve. Recently, ...various new classes of agents, which include next-generation androgen receptor (AR) signaling inhibitors (abiraterone, enzalutamide, apalutamide, and darolutamide), bone-targeting agents (radium-223 chloride, zoledronic acid), and poly(ADP-ribose) polymerase (PARP) inhibitors (olaparib, rucaparib, and talazoparib) have been developed to treat PCa. Agents targeting other signaling pathways, including cyclin-dependent kinase (CDK)4/6, Ak strain transforming (AKT), wingless-type protein (WNT), and epigenetic marks, have successively entered clinical trials. Furthermore, prostate-specific membrane antigen (PSMA) targeting agents such as
177
Lu-PSMA-617 are promising theranostics that could improve both diagnostic accuracy and therapeutic efficacy. Advanced clinical studies with immune checkpoint inhibitors (ICIs) have shown limited benefits in PCa, whereas subgroups of PCa with mismatch repair (MMR) or CDK12 inactivation may benefit from ICIs treatment. In this review, we summarized the targeted agents of PCa in clinical trials and their underlying mechanisms, and further discussed their limitations and future directions.
To reduce the risks and challenges faced by frontline workers in confined workspaces, accurate real-time health monitoring of their vital signs is essential for improving safety and productivity and ...preventing accidents. Machine-learning-based data-driven methods have shown promise in extracting valuable information from complex monitoring data. However, practical industrial settings still struggle with the data collection difficulties and low prediction accuracy of machine learning models due to the complex work environment. To tackle these challenges, a novel approach called a long short-term memory (LSTM)-based deep stacked sequence-to-sequence autoencoder is proposed for predicting the health status of workers in confined spaces. The first step involves implementing a wireless data acquisition system using edge-cloud platforms. Smart wearable devices are used to collect data from multiple sources, like temperature, heart rate, and pressure. These comprehensive data provide insights into the workers' health status within the closed space of a manufacturing factory. Next, a hybrid model combining deep learning and support vector machine (SVM) is constructed for anomaly detection. The LSTM-based deep stacked sequence-to-sequence autoencoder is specifically designed to learn deep discriminative features from the time-series data by reconstructing the input data and thus generating fused deep features. These features are then fed into a one-class SVM, enabling accurate recognition of workers' health status. The effectiveness and superiority of the proposed approach are demonstrated through comparisons with other existing approaches.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
This paper deals with the problem of estimating the parameters for fractional Ornstein–Uhlenbeck processes from discrete observations when the Hurst parameter
H is known. Both the drift and the ...diffusion coefficient estimators of discrete form are obtained based on approximating integrals via Riemann sums with Hurst parameter
H
∈
(1/2,
3/4). By adapting the stochastic integral representation to the fractional Brownian motion, these two estimators can be efficiently computed by the use of computer software. Numerical examples are presented to examine the performance of our method. An application to real data is also presented to show how to apply this method in practice.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Background
Ankylosing spondylitis (AS) is an autoimmune disease with a genetic correlation and is characterized by inflammation in the axial skeleton and sacroiliac joints. Many AS patients ...also have inflammatory bowel diseases (IBD), but the underlying causes of intestinal inflammation and osteoporosis in AS are not well understood. CX3CL1, a protein involved in inflammation, has been found to be up-regulated in AS patients and AS-model mice.
Methods
The authors investigated the effects of CX3CL1 on AS by studying its impact on macrophage polarization, inflammation factors, and osteoclast differentiation. Furthermore, the effects of inhibiting the NF-κB pathway and blocking CX3CL1 were assessed using BAY-117082 and anti-CX3CL1 mAb, respectively. AS model mice were used to evaluate the effects of anti-CX3CL1 mAb on limb thickness, spine rupture, and intestinal tissue damage.
Results
The authors found that CX3CL1 increased the expression of M1-type macrophage markers and inflammation factors, and promoted osteoclast differentiation. This effect was mediated through the NF-κB signaling pathway. Inhibition of the NF-κB pathway prevented M1-type macrophage polarization, reduced inflammation levels, and inhibited osteoclast differentiation. Injection of anti-CX3CL1 mAb alleviated limb thickness, spine rupture, and intestinal tissue damage in AS model mice by inhibiting M1-type macrophage polarization and reducing intestinal tissue inflammation.
Conclusions
The study demonstrated that up-regulated CX3CL1 promotes M1-type macrophage polarization and osteoclast differentiation through the NF-κB signaling pathway. Inhibition of this pathway and blocking CX3CL1 can alleviate inflammation and bone destruction in AS. These findings contribute to a better understanding of the pathogenesis of AS and provide a basis for clinical diagnosis and treatment.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Abstract
Using poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) as hole conductor, a series of inverted planar CH
3
NH
3
PbI
3−x
Cl
x
perovskite solar cells (PSCs) were fabricated ...based on perovskite annealed by an improved time-temperature dependent (TTD) procedure in a flowing nitrogen atmosphere for different time. Only after an optimum annealing time, an optimized power conversion efficiency of 14.36% could be achieved. To understand their performance dependence on annealing time, an
in situ
real-time synchrotron-based grazing incidence X-ray diffraction (GIXRD) was used to monitor a step-by-step gradual structure transformation from distinct mainly organic-inorganic hybrid materials into highly ordered CH
3
NH
3
PbI
3
crystal during annealing. However, a re-crystallization process of perovskite crystal was observed for the first time during such an annealing procedure, which helps to enhance the perovskite crystallization and preferential orientations. The present GIXRD findings could well explain the drops of the open circuit voltage (V
oc
) and the fill factor (FF) during the ramping of temperature as well as the optimized power conversion efficiency achieved after an optimum annealing time. Thus, the present study not only illustrates clearly the decisive roles of post-annealing in the formation of solution-processed perovskite to better understand its formation mechanism, but also demonstrates the crucial dependences of device performance on the perovskite microstructure in PSCs.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Abstract Deregulated microRNAs and their roles in cancer development have attracted much attention. Although miR-133a has been shown to be important in osteogenesis, its roles in osteosarcoma ...carcinogenesis and progression remain unknown. Hence, we focused on the expression and mechanisms of miR-133a in osteosarcoma development in this study. We found that miR-133a was downregulated in osteosarcoma cell lines and primary human osteosarcoma tissues, and its decrease was significantly correlated with tumor progression and prognosis of the patients. Functional studies revealed that restoration of miR-133a could reduce cell proliferation, promote cell apoptosis, and suppress tumorigenicity in osteosarcoma cell lines. Furthermore, bioinformatic prediction and experimental validation were applied to identify target genes of miR-133a, and the results revealed that the anti-tumor effect of miR-133a was probably due to targeting and repressing of Bcl-xL and Mcl-1 expression. Taken together, our data elucidate the roles of miR-133a in osteosarcoma pathogenesis and implicate its potential in cancer therapy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Axial spondyloarthritis (axSpA) is a chronic rheumatic disease predominantly characterized by inflammation and progressive structural damage. Patients are often diagnosed very late, which delays the ...optimal treatment period. Early diagnosis of axSpA, especially non-radiographic axSpA (nr-axSpA), remains a major challenge. This study aimed to investigate the diagnostic value of anti-Kaiso autoantibodies in axSpA and their correlation with clinical disease indicators.
Two pooled serum samples (seven patients with nr-axSpA and seven healthy controls) were profiled using HuProt arrays to investigate the diagnostic value of autoantibodies in nr-axSpA. Levels of anti-Kaiso autoantibodies in patients with axSpA and controls were determined using the Meso Scale Discovery assay system. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of anti-Kaiso autoantibodies in axSpA. Pearson's correlation was used to assess the correlation between anti-Kaiso autoantibodies and clinical parameters.
Seven candidate autoantibodies were present in the serum of patients with nr-axSpA. The levels of anti-Kaiso autoantibodies were significantly higher in the nr-axSpA group than in the other groups. It can differentiate nr-axSpA from ankylosing spondylitis (AS), healthy controls, and rheumatoid arthritis. The level of early-stage AS among patients with nr-axSpA decreased when they progressed to the late stage. Of all patients with axSpA, serum anti-Kaiso autoantibody levels were positively correlated with the C-reactive protein level and the Bath Ankylosing Spondylitis Disease Activity Index score and negatively correlated with disease duration.
Anti-Kaiso autoantibody may be a valuable diagnostic biomarker for early-stage AS in the nr-axSpA period and may be a potential therapeutic target.
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